A. Field of the Invention
The present invention relates to apparatus and methods for high-throughput, large-scale sample testing instrumentation, systems, and methods and, in particular, for evaluating and screening sample/environment interactions including but not limited to plants for rapid discovery of genotype-to-phenotype correlations at high spatial and temporal resolution.
B. Problems in the Art
Genes in plants respond to environmental conditions (e.g. temperature, light, CO2, salt, humidity, drought, pathogens, etc.). It is of great interest to discover phenotype/genotype relationships or other correlations based on environment conditions. A problem is that it is hard to analyze such things on large scale and in a fast time frame with resolution and precision. One approach is to grow a large number of plants in fields or greenhouses and try to measure phenotypic traits during their growth. This involves large amounts of growing space. It involves expensive labor and equipment to acquire data from the plants. It requires either reliance on nature for different growing conditions (e.g. grow the same plants in widely spaced fields to get different climates) or application of substantial amounts of growing factors (e.g. water, heat, etc.) in more controlled (e.g. greenhouse or plant growth chamber) structures. Both are expensive in terms of supplies, equipment, and labor, as well as energy costs. Both make it difficult to get fast acquisition of phenotype data.
Currently, plant phenomics studies rely mainly on culturing seeds and growing plants in soil pots and agarose plates using culture facilities (e.g., greenhouse and plant growth chamber) with controlled environments, and on using imaging technologies to measure plant characteristics and performance. While progress has been made, insufficient technical capacity imposes a strict limitation to conduct a large number of experiments for studying plant-environment interactions in a cost effective and timely manner. With the model plant Arabidopsis, for example, large-scale studies at high spatial/temporal resolution have been difficult for the cost and greenhouse needs, and thus, only few studies with a few thousand mutants have been done under specific environments.
Several high-throughput plant phenotyping facilities, such as the Australian Plant Phenomics Facility, Australian National University. Canberra, AU (see www.apf.anu.edu.au) and the PhenoFab® system in the Netherlands, (see www.keygene.com), are currently available for phenomics studies. Controlled environments and automated imaging analysis are the two main technologies involved in these plant phenotyping facilities. The controlled growth environmental conditions (e.g., temperature, light, humidity, CO2), provided by LemnaTec GmbH of Aachen, Germany (see, e.g., www.LemnaTec.com), are supported by a conveyor system for greenhouses and growth chambers. Specifically, the pots and plates with plants are moved through a growth compartment and scanned at preset time points from various angles to capture digital images. However, there are several concerns worth noting. First, screening of plant phenotypes using greenhouses or growth chambers is costly and the number of experiments is limited. Changing climate conditions of a greenhouse or plant growth chamber requires accessories such as a water spray system, heater, and air ventilation system. The flexibility, accuracy, and speed of changing environments are limited. These issues become exacerbated when multiple climate-controlled chambers are needed for growing plants in parallel under various environments (with each chamber providing a specific set of growth conditions). Second, due to the use of pots and plates, a relatively large amount of chemicals and biological species is needed. Energy consumption is another concern for using multiple growth chambers. Third, since current practices for monitoring root growth behaviors in laboratory are often limited to non-transparent soil pots and agarose plates, the resultant spatial resolution of morphological measurements for seed, root, and shoot phenotypes is on the millimeter scale. Microscopic real-time observation of cellular behaviors (e.g., cell division, elongation, host-pathogen interactions) on the micrometer resolution is not easy. Lastly, the low temporal resolution may lead to missing information about progressive and subtle changes in plant phenotypes during plant growth.
An example of issues with current methods is as follows.
Assume plant scientists want to develop new lines of corn that will better tolerate long stretches of hot, dry weather. How can they precisely assess the performance of those new plants in different environmental conditions? Field tests can provide some answers. Greenhouse tests can provide some more. But how can plant scientists get a true picture of a plant's growth and traits under a wide variety of controlled environmental conditions?
That has been too big and too precise for most laboratories. There are a few labs around the world that can do the work, but the studies are expensive, limited, and require time and labor. There has not been an accessible test instrument with enough scale, flexibility, and resolution to produce all the data scientists need.